In manufacturing facilities, the effective use of equipment is an important factor in determining operational performance and production line efficiency. With increased global competition, maximizing the efficiency of all assets within a manufacturing plant is key to determine economic viability. One commonly used measure to track equipment utilization is Overall Equipment Effectiveness (OEE). OEE is a measure of the time the equipment is used compared to the time the equipment is available. This value is then multiplied by the Quality %, the % of product produced that meets pre-determined quality control standards, to determine the % of time that the equipment is being used to produce good product:OEE=(Time Equipment is Operational)/(Time equipment is available)*(Quality %)
There are many ways to measure production line efficiency. One method is to manually time all the process steps required to produce product. This process is time consuming and prone to error. One of the simplest ways to measure production line efficiency is to measure the efficiency of the bottleneck operation. A bottleneck is a phenomenon where the performance or capacity of an entire system is limited by a single or limited number of components or resources. The term bottleneck is taken from the “assets are water” metaphor. As water is poured out of a bottle, the flow rate is limited by the width of the exit, that is, the bottleneck. By increasing the width of the bottleneck one can increase the rate at which the water flows out of the bottle. Such limiting components of a system are sometimes referred to as bottleneck points. In many production lines, the bottleneck operation can be traced to an operation performed on a given machine or piece of industrial equipment. The use of technology to acquire performance metrics from industrial equipment and to transmit these parameters to those responsible for equipment performance, possibly plant or operations managers or employees operating the equipment, has been available for many years. These systems are designed to communicate directly with the equipment's processor and PLCs (programmable logic controllers). This communication is typically referred to as Machine-to-Machine (M2M) communications. This information is typically transmitted to enterprise resource planning (ERP) software to be stored and analysed. The hardware infrastructure required to obtain this information is costly and software customization is required to be able to communicate with each piece of equipment.
The main elements involved in making M2M communication systems work are sensors, a wireless network and a computing device connected to the Internet. Typically, the sensors used in known M2M communications are those that can send telemetry data wirelessly.
M2M communication is generally referred to as “telemetry.” The concept of telemetry, where remote machines and sensors collect and send data to a central point for analysis, either by humans or computers, isn't new. New networking technology has allowed this concept to be taken to a new level.
Three very common technologies a) wireless sensors b) the Internet and c) computing devices, are coming together to create a new type of M2M communication. The use of such common technologies holds great promise in promoting telemetry's use by businesses, government and private individuals.
M2M communication systems can be used to more efficiently monitor critical public infrastructure, such as water treatment facilities or bridges, with less human intervention. M2M communications can help businesses maintain inventory or make it easier for scientists to perform research. Because this new form of M2M communications can rely on common technology, it is less cost prohibitive for smaller businesses.
M2M communication systems expand telemetry's role beyond its common use in science and engineering and places it in an everyday setting. People are already using M2M communications, but there are many more potential applications as wireless sensor technology, networks and computers improve and the concept is mated with other technology. M2M communications generally gather data and send it wirelessly to a network. It is then typically routed, often through the Internet, to a server or database. At the server or database, the data may be analyzed and acted upon, according to the software in place.
Older systems worked similarly, using “telemetry.” Telemetry technology, in many ways, was the forerunner of the more advanced M2M communications. Both telemetry communications and M2M communications collect data through sensors. The major difference between the two is that rather than a random radio signal typically used in telemetry communication, M2M communications use existing networks, such as wireless networks used by the public, to transmit the data.
In the past, telemetry communications were mostly used by scientists, governments and other organizations. Telemetry communications were used in applications as diverse as aerospace, agriculture, water treatment monitoring and wildlife science.
The sensors in known telemetry communications, however, were highly specialized and often needed high voltage or high current power sources to transmit data. Furthermore, data collection could be problematic if a remote sensor was located in a dead spot, which is a location where the sensor cannot transmit the data properly due to a lack of network coverage. In addition, the data analysis for these systems was conducted by what are now consider antiquated computers.
Modern M2M communications represent vast improvements over these systems. Remote sensor technology advances offer increased sensitivity and accuracy with lower voltage and current requirements. Analyzing computing devices and software also work at a faster pace. Also, with the advent of cloud computing, access to vast amounts of processing power is facilitated. The explosive growth of public wireless networks is likely the biggest change that has opened M2M communications to many more sectors.
Using wireless networks makes it easier to transmit telemetry for several reasons. Among other reasons, radio signals don't need to be as powerful as they once did, as cellular towers are densely spread over large areas to provide coverage and decrease the distance a signal must be transmitted. Known telemetry systems didn't always rely on radio signals, some used dedicated phone lines, for instance, but the wireless aspect allows for easier remote placement of sensors.
Known data acquisition systems track energy consumption for the purpose of minimizing energy use at peak hours. For example, U.S. patent application Ser. No. 12/429,821, filed Oct. 28, 2010 by Rockwell Automation Technologies Inc. entitled “Discrete energy assignments for manufacturing specifications”. However the system described in this patent application requires that the hardware and software need to be adapted to function with different equipment. The costs associated with the customisation of hardware and software for each piece of equipment make this type of system prohibitive to many potential users.
In addition to functional limitations, many known device networking, communication, and control systems are prohibitively expensive. Some systems require coupling complex electronics requiring significant processing and data storage capabilities into every device on the network. Other known systems require users to place full-scale servers in a home network to control the home devices on the network. Almost all known systems are too expensive for widespread adoption by most consumers, require excessive space, energy, and upkeep, and are too complicated to integrate into the manufacturing systems of many devices and appliances. This is especially true for manufacturing systems use to manufacture smaller or cheaper devices whose cost will increase by a proportionally greater fraction when the networking hardware and/or software are included.
The ability to provide the flow of actionable data from industrial equipment, including legacy equipment, to those responsible for the equipment in a relatively cost-effective and intuitive manner remains highly desirable.